single-au.php

IJAT Vol.5 No.5 pp. 679-687
doi: 10.20965/ijat.2011.p0679
(2011)

Paper:

Compensation of Thermo-Dependent Machine Tool Deformations Due to Spindle Load Based on Reduced Modeling Effort

Christian Brecher and Adam Wissmann

Laboratory for Machine Tools and Production Engineering, RWTH Aachen University, Manfred-Weck Haus, 19 Steinbachstrasse, Aachen 52074, Germany

Received:
March 30, 2011
Accepted:
May 18, 2011
Published:
September 5, 2011
Keywords:
machine tool, thermal behavior, modeling, compensation, transfer function
Abstract
This paper presents the continuance of the scientific work on compensation of thermo-dependent machine tool deformations due to spindle load in consideration of rough machining. After the development of an indirect compensation method, based on a transfer function using a third order time delay element, further works have been focused on the reduction of the modeling effort. The reduction of the modeling effort makes the developed compensation approach suitable for the industry. The thermo-dependent behavior of machine tools is strongly non-linear. Hence, modeling in several operating points is essential. Primarily, the investigated machine tool wasmodeled by using six spindle speed levels. Due to different possible torques at every speed level, the power spectrum of the spindle was divided into four power levels. Thus, the starting point was the modeling of thermo-dependent machine tool deformation by executing 24 experiments. The appropriate compensation results were very satisfactory. The aim of the presented work is a compensation result of similar performance achieved by noticeable lower modeling effort. In the first step, the thermal behavior of the investigated milling machine is analyzed. The analysis affects the choice of adequate speed and power levels for modeling. According to previous results, the chosen transfer function is a third order time delay element. The performance of the compensation method based on a reduced number of models is validated on two different speed / power spectra. The final comparison of the compensation results regarding root mean square errors presents the benefit.
Cite this article as:
C. Brecher and A. Wissmann, “Compensation of Thermo-Dependent Machine Tool Deformations Due to Spindle Load Based on Reduced Modeling Effort,” Int. J. Automation Technol., Vol.5 No.5, pp. 679-687, 2011.
Data files:
References
  1. [1] C. Brecher, F. Hoffmann, T. Gerrath, L. Schapp, M. Weck, and P. Hirsch, “Messtechnische Untersuchung von Prozess und Maschine, Beurteilung und Abnahme von Werkzeugmaschinen (ab 1960),” in: M. Weck (Ed.) 100 Jahre Produktionstechnik, Springer-Verlag, Berlin Heidelberg, pp. 437-448, 2006.
  2. [2] G. Spur, E. Hoffmann, Z. Palunicic, K. Benzinger, and H. Nymoen, “Thermal Behaviour Optimization ofMachine Tools,” Annals of the CIRP Manufacturing Technology, Vol.37, pp. 401-405, 1988.
  3. [3] K. Großmann and G. Jungnickel, “Prozessgerechte Bewertung des thermischen Verhaltens von Werkzeugmaschinen,” first (Ed.) Technische Universität Dresden, Dresden, 2006.
  4. [4] R. Ichimiya, K. Yokoyama, and Y. Watanabe, “Experimental Study on Thermal Deformations of Machine Tool,” first (Ed.) Niigita University, Niigita, 1976.
  5. [5] U. Heisel, “Ausgleich thermischer Deformationen an Werkzeugmaschinen,” first (Ed.) Technische Universität Berlin, Berlin, 1980.
  6. [6] J. Yang, “Thermal Error Mode Analysis and Robust Modelling for Error Compensation on a CNC Turning Centre,” Int. J. of Machine Tools & Manufacture, Vol.39, pp. 1367-1381, 1999.
  7. [7] D. S. Lee, J. Y. Choi, and D. H. Choi, “ICA Based Thermal Source Extraction and Thermal Distortion Compensation Method for a Machine Tool,” Int. J. of Machine Tools & Manufacture, Vol.43, pp. 589-597, 2003.
  8. [8] S. R. Postlethwaite, “The Use of Thermal Imaging, Temperature and Distortion Models for Machine Tool Thermal Error Correction,” Proc. of the institution of mechanical engineers, Vol.212, pp. 671-679, 1998.
  9. [9] C. Lo, J. Yuan, and J. Ni, “Optimal Temperature Variable Selection by Grouping Approach for Thermal Error Modelling and Compensation International,” J. of Machine Tools and Manufacture, Vol.39, pp. 1383-1396, 1999.
  10. [10] J. S. Chen, “Neural network-based modelling and error compensation of thermally-induced spindle errors,” The Int. J. of Advanced Manufacturing Technology, Vol.12, pp. 303-308, 1996.
  11. [11] M. Mitsuishi, T. Okumura, T. Nagao, and Y. Hatamura, “Active Thermal Deformation Compensation Based on Internal Monitoring and a Neural Network,” Advancement of intelligent production, pp. 215-220, 1994.
  12. [12] C. D. Mize and J. C. Ziegert, “Neural network thermal error compensation of a machining center,” Precision engineering, Vol.24, pp. 338-346, 2000.
  13. [13] N. Srinivasa and J. C. Ziegert, “Automated measurement and compensation of thermally induced error maps in machine tools,” Precision engineering, Vol.19, pp. 112-132, 1996.
  14. [14] U. Heisel and T. Stehle, “Fuzzy-Logik zur Bestimmung des thermischen Verhaltens. Berechnung thermischer Verlagerungen an Werkzeugmaschinen und Möglichkeiten zur Kompensation Teil 2,” Die Maschine, 51, pp. 52-56, 1997.
  15. [15] J.-H. Lee and S.-H. Yang, “Thermal ErrorModeling of a Horizontal Machining Center Using Fuzzy Logic Strategy,” J. of Manufacturing Processes, Vol.3, pp. 120-127, 2001.
  16. [16] K.-C. Wang, P.-C. Tseng, and K.-M. Lin, “Thermal Error Modeling of a Machining Center Using Grey System Theory and Adaptive Network-Based Fuzzy Inference System,” Int. J. Series C Mechanical Systems, Machine Elements and Manufacturing, Vol.49, pp. 1179-1187, 2006.
  17. [17] T. Moriwaki and E. Shamoto, “Analysis of Thermal Deformation of an Ultra Precision Air Spindle System,” CIRP Annals, Vol.47, pp. 283-286, 1996.
  18. [18] C. Brecher, P. Hirsch, and M. Weck, “Compensation of Thermoelastic Machine Tool Deformation Based on Control internal Data,” CIRP Annals, Vol.53, pp. 299-304, 2004.
  19. [19] O. Horejs, M. Mares, P. Kohut, P. Barta, and J. Hornych, “Compensation of Machine Tool Thermal Errors Based on Transfer Functions,” MM Science J., pp. 162-165, 2010.
  20. [20] S. Fraser, M. Attia, and M. Osman, “Modelling, Identification and Control of Thermal Deformation of Machine Tool Structure, Part 1: Concept of Generalized Modelling,” J. of Manufacturing Science and Engineering, Vol.120, pp. 623-631, 1998.
  21. [21] T. Moriwaki, “Thermal Deformation and Its On-Line Compensation of Hydrostatically Supported Precision Spindle,” Annals of the CIRP, Vol.37, pp. 393-396, 1988.
  22. [22] J. S. Chen, J. X. Yuan, J. Ni, S. M. Wu, “Real-time compensation for time-variant volumetric errors on a machining center,” J. of Engineering for Industry, Vol.115, pp. 472-479, 1993.
  23. [23] K. Grosmann and G. Jungnickel, “Genauigkeitssteigerung an Werkzeugmaschinen,” ZWF, 94, pp. 320-323, 1999.
  24. [24] C. Brecher and A. Wissmann, “Stressing Unit for Modelling of Thermal Behaviour of a Milling Machine,” Proc. of the 12th CIRP Conf. on Modelling of Machining Operations, pp. 727-730, 2009.
  25. [25] C. Brecher and A.Wissmann, “Modelling of Thermal Behaviour of a Milling Machine Due to Spindle Load,” Proc. of the 12th CIRP Conf. on Modelling of Machining Operations, pp. 673-678, 2009.
  26. [26] C. Brecher and A. Wissmann, “Optimierung des thermischen Verhaltens von Fräsmaschinen,” Zeitschrift für wirtschaftlichen Fabrikbetrieb, Vol.6, pp. 437-441, 2009.
  27. [27] D. Abel, “Regelungstechnik,” 33th (Ed.) Verlag Mainz, Aachen, 2009.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Oct. 11, 2024